Relationship Information Propagation
In this project, we study two tightly coupled topics in online social networks (OSN): relationship classification and information propagation. The links in a social network often reflect
social relationships among users. In this work, we first investigate identifying the relationships among social network users based on certain social network property and limited pre-known information. Social networks have
been widely used for online marketing. A critical step is the propagation maximization by choosing a small set of seeds for marketing. Based on the social relationships learned in the first step, we show how to exploit these
relationships to maximize the marketing efficacy. We evaluate our approach on large scale real-world data from Renren network, confirming that the performances of our relationship classification and propagation maximization
algorithm are pretty good in practice.
Relationship Classification in Large Scale Online Social Networks and Its Impact on Information Propagation (IEEE INFOCOM 2011).
Copyright © 2010,
Wireless Networking Research Lab, Department of Computer
Science, Illinois Institute of Technology